IJSER Home >> Journal >> IJSER
International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 3    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 3, March 2011 Edition
Parameter Ranking and Reduction in Communication Systems
Full Text(PDF, 3000)  PP.  
M.H. Azmol, M.H. Biswas, and A. Munnujahan
Eigenvalues, Parameter reduction, Non-negative matrix factorization
Parameter reduction from experimental data is an important issue arising in many frequently encountered problems with different types of applications in communications engineering. However, the computational effort grows drastically with the number of parameters in such types of applications. This paper proposes a technique that reduces the performance parameters of a communication system based on eigenvalues of covariance matrix as well as providing a weighted rank of parameters by an approach called non-negative matrix factorization (NMF). The factorization of original matrix provides a weight metric that offers a means of ranking and selecting meaningful important parameters. The relative importance of each parameter is measured from the sequentially ordered eigenvalues. The main aims of this paper are to determine, identify and reduce the reasonable number of performance parameters which will reflect the best measurement system of a describing network scenario.
[1] IEEE 802.11 WG, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, IEEE Std. 802.11, Aug. 1999.

[2] K.V.R. Kanth, D. Agarwal, A.E. Abbadi, & A. Singh, “Dimensionality Reduction for Similarity Searching in Dynamic Databases,” ACM SIGMOD Conference Proceeding, pp. 166-176, 1998.

[3] Ye J. Janardan, R. Li, “An Efficient Dimension Reduction Scheme for Image Compression and Retrieval,” ACM SIGKDD Conference Proceedings. 2004.

[4] P. Mitra, C.A. Murthy, K. Sankar Pal, “Unsupervised Feature Selection Using Feature Similarity,” IEEE transaction on pattern analysis and machine intelligence. vol. 24, no 3, march 2002.

[5] M. Berrya, M. Brownea, A.N. Langvilleb, V.P. Paucac, R.J. Plemmonsc, “Algorithms and Applications for Approximate Nonnegative Matrix Factorization,” Computational Statistics and Data Analysis 52. pp. 155-173, 2007.

[6] J. Shlens, “A Tutorial on Principal Component Analysis”, Center for Neural Science, New York City, NY 10003-6603, April 22, 2009.

[7] I.T. Jolliffe, “Principal Component Analysis,” Springer-Verlag, New York, 2002.

[8] M.A. Hasan, “Low Rank Approximations with Applications to Principal Singular Component Learning Systems,” Proceedings of the 47th IEEE Conference on Decision and Control, Cancun Mexico, Dec. 9-11, 2008.

[9] H.H. Harman, Modern Factor Analysis. 3rd Ed. Chicago: University of Chicago Press, 1976.

[10] Y. Jieping , “Generalized Low Rank Approximations of Matrices,” Proceedings of the 21st International Conference on Machine Learning. 2004.

[11] B.C. Moore, “Principal Component Analysis in Linear Systems: Controllability, Observability, and Model Reduction,” IEEE Transactions on Automatic Control 26 (1), 17-32, 1981.

[12] J. Hahn, T.F. Edgar, W. Marquardt, “Controllability and Observability Covariance Matrices for the Analysis and Order Reduction of Stable Nonlinear Systems,” Journal of Process Control , 13, 115-127, 2003.

[13] S. Lall, J.E. Marsden, S. Glavaski, “Empirical Model Reduction of Controlled Nonlinear Systems,” 14th IFAC World Congress, Beijing, 1999.

[14] C. Sun, J. Hahn, “Reduction of Differential-Algebraic Equation Systems Via Projections and System Identification,” Journal of Process Control, 15, 639-650, 2005.

[15] C.L. Sun, J. Hahn, “Parameter Reduction for Stable Dynamical Systems Based on Hankel Singular Values and Sensitivity Analysis,” Chem. Eng.Sci., 61(16), pp. 5393–5403, 2006.

[16] H. Castel-Taleb, L. Mokdad, “Performance Measure Bounds in Mobile Networks by State Space Reduction,” Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS’ 05), 2005.

[17] A. Lakhina, K. Papagiannaki, M Crovela, C. Diot, Eric D. Kolaczyk, N. Taft, “Structural Analysis of Network Traffic Flows,” SIGMETRICS/Performance. New York, NY, USA, June 12–16, 2004.

[18] Y. Nasr Harandi, M. Yaghoubi Waskasi, M. Pirhadi, M. Mirzabaghi, A. Iravani Tabrizipoor, “ A Test Methodology for Testing Next Generation Broadband IP Access Services,” International Conference on Advanced Communication Technology (ICACT 2007), Seoul, Korea, Feb. 2007.

[19] S.M.R. Sadri, M.Pirhadi, Y. N. Harandi, M.Y. Waskasi, A.I. Tabrizipoor, M. Mirzabaghi, “ Test Strategy For DSL Broadband IP Access Services,” Highcapacity Optical Networks and Enabling Technologies (HONET 2007), Dubai UAE, Nov. 2007

[20] D. Lee, H. Seung, “Algorithms for Non-Negative Matrix Factorization,” Adv. Neural Inform. Process. Systems 13, pp. 556-562, 2001.

Untitled Page